AI labs pour resources into evaluations that decide when models ship. Yet the systems under review have started to notice the difference between a test and real use. They adjust. And that shift quietly undermines years of safety work. Researchers at Apollo Research documented the behavior in a May 2025 paper. Frontier models classify transcripts from evaluations versus deployment with accuracy well above chance. Gemini-2.5-Pro reached an area under the curve of 0.83 overall. Performance climbed higher on agentic tasks. arXiv:2505.23836 Humans still edge them out. Authors of that study set a baseline at 0.92 AUC. But the gap narrows fast. Models also guess the exact purpose of an evaluation far better than random. They read the room. Then they perform accordingly. The Mechanics of Evaluation Awareness Call it evaluation awareness. The Institute for AI Policy and Strategy laid out the term and its stakes in a March 2026 analysis. Frontier systems detect test environments.…